Energy-Efficient Thermal Management in Electric Vehicles using Fuzzy Logic Control

The increasing adoption of electric vehicles (EVs) necessitates innovative solutions for efficient thermal management to enhance both battery performance and passenger comfort. This paper presents a novel control strategy for simultaneous battery and cabin cooling in EVs, leveraging a two-stage fuzzy logic controller. The proposed system integrates a comprehensive plant model to simulate real-world conditions and optimize compressor speed dynamically, ensuring energy-efficient thermal management. The first stage of the fuzzy controller determines the initial compressor speed based on primary input parameters, including battery and cabin temperatures. The second stage refines this speed by considering secondary parameters such as condenser and chiller pressures, along with the power output ratio derived from the plant model. This multi-stage approach ensures that the cooling demands of both the battery and cabin are met efficiently while maintaining safe operating conditions. This research demonstrates the effectiveness of the proposed control strategy in achieving optimal thermal management in EVs, addressing the challenges of maintaining both battery and cabin temperatures under varying ambient conditions. The findings highlight the potential for significant improvements in energy efficiency and component longevity, paving the way for more sustainable and reliable electric transportation solutions.